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Prediction of the potential ecological niche of the ladybugs Cycloneda sanguinea (Linnaeus, 1763) (Coleoptera: Coccinellidae) based on current and future scenarios of climate change using the MaxEnt model.

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Title: Prediction of the potential ecological niche of the ladybugs Cycloneda sanguinea (Linnaeus, 1763) (Coleoptera: Coccinellidae) based on current and future scenarios of climate change using the MaxEnt model.
Authors: Barros, Emerson Cristi de1 (AUTHOR) emerson.barros@ufv.br, Sacramento, Jose Augusto Amorim Silva do2 (AUTHOR), Taube, Paulo Sergio3 (AUTHOR), da Paixão, Gefferson Pereira1 (AUTHOR), Santos, Elaine4 (AUTHOR)
Source: Biocontrol Science & Technology. Nov2025, Vol. 35 Issue 11, p1233-1250. 18p.
Subject Terms: *CLIMATE change, *ECOLOGICAL niche, *CLIMATE change detection, *LADYBUGS, *HABITAT suitability index models, *BIOGEOGRAPHY
Geographic Terms: SOUTH America
Abstract: Climate change impacts the geographic distribution of species, influencing ecological interactions, biological control, and suitable areas for insect occurrence. Models like MaxEnt help predict these changes. Global occurrence data for Cycloneda sanguinea (Linnaeus, 1763) (Coleoptera: Coccinellidae) were obtained from GBIF and SpeciesLink, with 1960 occurrences used after filtering. The spThin package was used to avoid spatial autocorrelation. Bioclimatic variables were sourced from the WorldClim database, and future SSP1-2.6 and SSP5-8.5 scenarios were used for projections. Ecological niche models were generated using MaxEnt. The best model for the distribution of C. sanguinea was selected using the Akaike Information Criterion (AIC) and the Boyce index, with a feature classes PT and regularisation multiplier of 2. The main contributing bioclimatic variables included temperature and precipitation, with BIO_10 (Mean Temperature of the Warmest Quarter) and BIO_8 (Mean Temperature of the Wettest Quarter) standing out. Future scenarios predicted both expansion and contraction of suitable areas, with greater expansion in the SSP5-8.5 scenario. In 2050, the expansion of suitable areas will occur in the northern and northeastern regions of South America, while contraction will affect central and northeastern regions. The study highlighted the need for future models to consider additional factors, such as vegetation, presence of rivers and lakes, target pests, other natural enemies, and insecticide effects, to improve accuracy and predictive power. [ABSTRACT FROM AUTHOR]
Database: Academic Search Index
Description
Abstract:Climate change impacts the geographic distribution of species, influencing ecological interactions, biological control, and suitable areas for insect occurrence. Models like MaxEnt help predict these changes. Global occurrence data for Cycloneda sanguinea (Linnaeus, 1763) (Coleoptera: Coccinellidae) were obtained from GBIF and SpeciesLink, with 1960 occurrences used after filtering. The spThin package was used to avoid spatial autocorrelation. Bioclimatic variables were sourced from the WorldClim database, and future SSP1-2.6 and SSP5-8.5 scenarios were used for projections. Ecological niche models were generated using MaxEnt. The best model for the distribution of C. sanguinea was selected using the Akaike Information Criterion (AIC) and the Boyce index, with a feature classes PT and regularisation multiplier of 2. The main contributing bioclimatic variables included temperature and precipitation, with BIO_10 (Mean Temperature of the Warmest Quarter) and BIO_8 (Mean Temperature of the Wettest Quarter) standing out. Future scenarios predicted both expansion and contraction of suitable areas, with greater expansion in the SSP5-8.5 scenario. In 2050, the expansion of suitable areas will occur in the northern and northeastern regions of South America, while contraction will affect central and northeastern regions. The study highlighted the need for future models to consider additional factors, such as vegetation, presence of rivers and lakes, target pests, other natural enemies, and insecticide effects, to improve accuracy and predictive power. [ABSTRACT FROM AUTHOR]
ISSN:09583157
DOI:10.1080/09583157.2025.2558960